Machine Learning Engineer Part Time Jobs in Winnipeg, MB

The Solution Analyst II will be part of the Life IS Core team and will contribute to Wawanesa's success by applying strong analysis, problem-solving, communication, and collaboration skills to operational work across core Life systems.
The ideal candidate is curious, adaptable, and comfortable working in an environment that balances planned work with changing production priorities. They ask effective questions, organize incomplete or conflicting information, learn unfamiliar business processes and technologies, and turn findings into clear recommendations and actions. The candidate must have analyst experience related to Business, Systems, and/or Quality.
Key responsibilities include collaborating with business stakeholders, developers, analysts, architects, vendors, and support teams to:
   Understand problems, assess business impact, and recommend practical next steps.
   Take assigned operational work from intake through resolution or escalation.
   Learn from recurring issues and improve how the team analyzes, documents, tests, and supports Life Core systems.
The successful candidate will demonstrate sound judgment, learning agility, attention to detail, and AI literacy. They can use approved AI-assisted tools responsibly to support analysis and decision-making, validate outputs against reliable sources, and recognize when human review or escalation is required. Technical skills such as SQL and an understanding of integrated data flows will support the work but are not a substitute for fundamental analyst skills.

• Analyze recurring issues and patterns using available evidence, including application behavior, documentation, logs, monitoring, queries, integration payloads, batch results, and data flows. Recommend permanent fixes, automation opportunities, monitoring improvements, or process changes based on frequency, actionability, and business impact.
• Learn the business processes, systems, data, and technologies needed to analyze unfamiliar issues. Connect information across policy administration, claims, commissions, billing, reinsurance, and reporting processes.
• Investigate incidents, service requests, errors, and production issues. Ask effective questions, gather evidence, distinguish symptoms from causes, and establish business impact, expected and actual behavior, timing, scope, and reproducibility.
• Organize findings into clear problem statements, requirements, acceptance criteria, solution options, recommendations, and appropriately sized work items for technical and non-technical audiences.
• Create test scenarios, assess regression risk, validate fixes and small enhancements, and support business verification, controlled implementation, and post-production validation.
• Own assigned operational work through restoration, resolution, or escalation. Keep records current, communicate status and workarounds, coordinate next steps, and confirm service stability before closure.
• Collaborate with business stakeholders, developers, analysts, architects, vendors, integration teams, and support teams to resolve issues and make dependencies and decisions visible.
• Create and maintain support procedures, troubleshooting guidance, knowledge articles, and handover documentation that reduce repeat effort and key-person dependency.
• Use approved AI-assisted tools to strengthen analysis, explore alternatives, create structured work items and test scenarios, and identify edge cases. Validate outputs against source information and established controls.
• Participate in operational standups, queue and backlog prioritization, incident reviews, sprint planning, reviews, and retrospectives. Balance interrupt-driven support with planned delivery.

• Minimum 3 years of experience in systems analysis, business analysis, quality analysis, or application support.
• Completion of a post-secondary degree/certificate or equivalent experience.
• Strong foundational analysis, problem-solving, communication, and collaboration skills. The candidate can gather and assess evidence, identify gaps and assumptions, connect information across business processes and systems, develop supported recommendations, and explain findings and practical next steps to technical and non-technical stakeholders.
• Curiosity and learning agility. The candidate can ask effective questions, seek and apply feedback, and become productive with unfamiliar business domains, systems, data, and technologies.
• Sound judgment, ownership, planning, and attention to detail in an interrupt-driven environment. The candidate can prioritize changing work, keep multiple items current, maintain accurate evidence and records, share knowledge, and escalate when appropriate.
• Demonstrated AI literacy, including the ability to use approved AI-assisted tools to improve analysis, troubleshooting, testing, or work-item quality while validating outputs, protecting information, and applying human judgment.
• Experience supporting production applications in a BAU, incident-management, or service-operations environment using agile or continuous-delivery practices.
• Working knowledge of SQL and relational data concepts, with the ability to interpret queries and reconcile information across integrated applications, APIs, batch processes, logs, and monitoring output.
• Assets include experience with service-management and work-tracking tools such as ServiceNow and Jira, Confluence or similar knowledge-management tools, .NET application architecture, scripting or automation, and insurance or broker industry knowledge.